Neural-networks-based edges selector for boundary extraction problems
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摘要
In the present work, a neural-networks-based system is presented that makes it possible to reduce, when generating edge maps to be used in an object boundary detection problem, the number of edges that are not due to the object itself, but to the background. Starting from a conventional edge detection, the selection is carried out by a neural-networks-based classifier, which is trained using examples. As a test for the system, the application to bovine livestock images (from which we want to extract the boundary of the animal) is presented.
论文关键词:Edge detection,Edge selection,Boundary extraction,Neural networks
论文评审过程:Received 5 February 2004, Accepted 27 May 2004, Available online 27 July 2004.
论文官网地址:https://doi.org/10.1016/j.imavis.2004.05.005